Kasvuvalos combines AI-assisted scenario analysis with years of market data background testing. The platform supports decision-making and reduces the share of emotion-based guessing, but always leaves the final decision to the user.
Start the analysisThe view describes the user interface of the platform: analysis of market data, volatility indicators and position-specific risk limits in the same view.
Kasvuvalos transforms market volatility into structured data. The platform does not make predictions without grounds: each recommendation goes through algorithmic validation before it is presented to the user.
The basis has historical testing that spans several market cycles – up, down and sideways periods. This reveals how the strategy would have behaved under different conditions before applying it to live data.
All strategies are first tested against historical market data. The focus is on risk management: the goal is to reduce the biggest loss periods, not just to maximize returns.
Let's track the biggest historical decline in equity and compare it to a benchmark strategy.
The position size adjusts according to market fluctuations to stabilize it.
There is a predefined maximum loss for each open position.
Performance is broken down by stages of the market cycle, not just total return.
Metrics are based on historical data and background testing. Historical returns are not a guarantee of future performance, and actual results depend on the instrument used, the market situation and the user's own limitations.
The process has been kept transparent so that the user understands what each recommendation is based on.
Market data, order books and volatility signals are constantly compiled from multiple sources.
The model compares the current situation with historical patterns and evaluates several likely developments.
The user receives a structured recommendation with risk parameters - the final decision remains with him.
For the short-term trader, the platform recognizes anomalous volatility and suggests a position size that matches the user's risk limits. Manual monitoring from multiple screens is reduced when signals are gathered in one view.
For the user with a longer investment horizon, the platform offers regular portfolio rebalancing suggestions based on historical correlation and risk analysis. This reduces the need to go through market data manually every week.
Kasvuvalos is built on the idea that the model supports professional judgment - it does not replace it. The recommendations are always justified with visible metrics, so that the user can evaluate the logic himself.
The focus is on capital protection: before seeking returns, the platform aims to limit risk and identify situations where market data does not support a clear recommendation.
Market data is updated on the platform within seconds, depending on the source. Latency varies slightly depending on the instrument and the API integration used, and this is transparent to the user in the timestamps of the view.
The training data consists of historical market data from multiple instruments and time frames. The model is updated regularly, and the changes are documented so that the results of background testing remain traceable.
Connections are implemented through API integrations to the most common trading platforms and data sources. The scope of the integration is adjusted on a case-by-case basis according to the user's current tool stack.
Make an appointment for a demo and go through how background testing and risk management would work for your own portfolio or trading style.
Request a demoKasvuvalos is aimed at professional and serious day traders who value trackable, data-driven decision making.